Improvement of the agronomic characteristics of crop plants has been ongoing since the beginning of agriculture. Most of the land suitable for crop production is currently being used. As human populations continue to increase, improved crop varieties will be required to adequately provide food and feed (Trewavas, 2001). To avoid catastrophic famines and malnutrition, future crop cultivars will need to have improved yields with equivalent farm inputs. These cultivars will need to more effectively withstand adverse conditions such as drought, soil salinity, and disease, which will be especially important as marginal lands are brought into cultivation. Finally, cultivars are needed with altered nutrient composition to enhance human and animal nutrition. To allow for more efficient food and feed processing, cultivars can be designed for specific end-uses. For all these uses, identification of the genes controlling phenotypic expression of traits of interest will play a role in accelerating development of superior crop germplasm by conventional or transgenic approaches.
A number of highly efficient approaches are available to assist identification of genes playing key roles in expression of agronomically important traits, including genetics, genomics, bioinformatics, and functional genomics. Genetics is the scientific study of the mechanisms of inheritance. By identifying mutations that alter a pathway or response of interest, classical (or forward) genetics can help identify genes involved in these pathways or responses. Genetics is also the central component in improvement of germplasm by breeding. Through molecular and phenotypic analysis of genetic crosses, loci controlling traits of interest can be mapped and followed in subsequent generations. Knowledge of the genes underlying phenotypic variation between crop accessions can facilitate the development of markers that greatly increase the efficiency of the germplasm improvement process as well as open avenues for discovery of additional superior alleles.
Genomics is the system-level study of an organism's genome, including genes and the corresponding gene products: RNA and polypeptides. At a first level, genomic approaches have provided large datasets of sequence information from diverse plant species, including full-length and partial cDNA sequences and the complete genomic sequence of a model plant species, Arabidopsis thaliana. Recently, the first draft sequence of a crop plant's genome, that of rice (Oryza sativa), has also become available (see Goff et al., 2002). The availability of a whole genome sequence makes possible the development of tools for system-level study of other molecular complements, such as by using arrays and chips to determine the complement of expressed genes in an organism under specific conditions. Such data can be used as a first indication of the potential for certain genes to play key roles in expression of different plant phenotypes. Bioinformatics approaches interface directly with first-level genomic datasets in allowing for the identification of sequences of interest by annotative or other means. Using, for example, similarity searches, alignments, and phylogenetic analyses, bioinformatics can often identify homologs of a gene product of interest. Very similar homologs (for example, greater than about 90% amino acid identity over the entire length of a polypeptide) are likely to be orthologs; that is, they are likely to share the same function in different organisms.
Functional genomics can be defined as the assignment of functions to genes and gene products. Functional genomics draws from genetics, genomics, and bioinformatics to derive a path toward identifying genes involved in a particular pathway or response of interest. Expression analysis, for example, uses high density DNA microarrays (often derived from genome-scale organismal sequencing) to monitor the mRNA expression of thousands of genes in a single experiment. Experimental treatments can include those eliciting a response of interest, such as the drought resistance response in plants subjected to low water conditions. To give additional examples of the use of microarrays, mRNA expression levels can be monitored in distinct tissues over a developmental time course, or in mutants affected in a response of interest.
Proteomics can also help to assign function by assaying the expression and post-translational modifications of hundreds of polypeptides in a single experiment. Proteomics approaches are in many cases analogous to the approaches taken for monitoring mRNA expression in microarray experiments. Polypeptide-polypeptide interactions can also help to assign polypeptides to a given pathway or response by identifying polypeptides which interact with known components of the pathway or response. For functional genomics, polypeptide-polypeptide interactions are often studied using large-scale yeast two-hybrid assays. Another approach to assigning gene function is to express the corresponding polypeptide in a heterologous host, for example the bacterium Escherichia coli, followed by purification and enzymatic assays of the purified polypeptide.
Ultimately, demonstration of the ability of a gene-of-interest to control a given trait is derived from experimental testing in a plant species of interest. The generation and analysis of plants that are transgenic for a gene of interest can be used for plant functional genomics, with several advantages. The gene can alternatively be either overexpressed (via transgenesis) or underexpressed (“knocked out”), thereby increasing the chances of observing a phenotype linking the gene to a pathway or response of interest.
Two aspects of transgenic functional genomics help lend a high level of confidence to functional assignments derived from this approach. First, phenotypic observations are carried out in the context of the living plant. Second, the range of phenotypes observed can be checked and correlated with the observed expression levels of the introduced transgene. Transgenic functional genomics is especially valuable in improved cultivar development. Only genes that function in a pathway or response of interest and that in addition are able to confer a desired trait-based phenotype are promoted as candidate genes for crop improvement efforts. In some cases, transgenic lines developed for functional genomics studies can be directly utilized in the initial stages of product development.
Another approach towards plant functional genomics involves first identifying plant lines with mutations in specific genes of interest, followed by phenotypic evaluation of the consequences of such gene knockouts on the trait under study. Such an approach reveals genes essential for the expression of specific traits.
Genes identified through functional genomics can be directly employed in efforts towards germplasm improvement by transgenic approaches as disclosed above, or used to develop markers for identification and tracking of alleles-of-interest in mapping and breeding populations. Knowledge of such genes can also enable the construction by any of a number of molecular methods of superior alleles that are non-existent in nature.
Therefore, the identification of genes that can be used for crop and germplasm improvement is needed. This and other needs in the art are addressed by the present disclosure.